title: Red cell distribution width as a bleeding predictor after percutaneous coronary intervention.
abstract: BACKGROUND
  Red cell distribution width (RDW), a measure of variability in the size of circulating erythrocytes, is an independent predictor of mortality in cardiovascular disease and in patients undergoing percutaneous coronary intervention (PCI). We set out to determine if RDW is a prognostic marker of major bleeding post-PCI.
  
  
  METHODS
  The study population included 6,689 patients who were subjected to PCI. The RDW was derived from a complete blood count drawn before PCI. Major inhospital bleeding was defined as a hematocrit decrease ≥12%, hemoglobin drop of ≥4, transfusion of ≥2 units of packed red blood cells, retroperitoneal, or gastrointestinal or intracranial bleeding. Multivariable logistic analysis of major inhospital bleeding was performed using a logistic regression model that comprised the National Cardiovascular Data Registry (NCDR) risk score model as a single variable.
  
  
  RESULTS
  Major bleeding (P < .001), vascular complications (P = .005), and transfusions (P < .001) were significantly higher in patients with higher baseline RDW values. After adjustment for known bleeding correlates, RDW was a significant predictor for major bleeding (odds ratio 1.12, 95% CI 1.06-1.19, P < .001). Although the c statistic of the NCDR risk prediction model changed from 0.730 to 0.737 (P = .032), the net reclassification improvement increased significantly after the addition of RDW as a continuous variable (17.3% CI 6.7%-28%, P = .002).
  
  
  CONCLUSIONS
  Red cell distribution width, an easily obtainable marker, has an independent, linear relationship with major bleeding post-PCI and incrementally improves the well-validated NCDR risk prediction model. These data suggest that further investigation is necessary to determine the relationship of RDW and post-PCI bleeding.
authors.affiliation: MedStar Washington Hospital Center, Washington, DC 20010, USA.
authors.forename: Omid
authors.initials: O
authors.lastname: Fatemi
authors.forename: Rebecca
authors.initials: R
authors.lastname: Torguson
authors.forename: Fang
authors.initials: F
authors.lastname: Chen
authors.forename: Soha
authors.initials: S
authors.lastname: Ahmad
authors.forename: Salem
authors.initials: S
authors.lastname: Badr
authors.forename: Lowell F
authors.initials: LF
authors.lastname: Satler
authors.forename: Augusto D
authors.initials: AD
authors.lastname: Pichard
authors.forename: Neal S
authors.initials: NS
authors.lastname: Kleiman
authors.forename: Ron
authors.initials: R
authors.lastname: Waksman
mesh_terms: D000368:Aged; D003324:Coronary Artery Disease / Q000097:blood / Q000601:surgery*; D004906:Erythrocyte Count; D004912:Erythrocytes; D005260:Female; D005500:Follow-Up Studies; D006801:Humans; D008297:Male; D008875:Middle Aged; D062645:Percutaneous Coronary Intervention; D011182:Postoperative Care / Q000379:methods*; D019106:Postoperative Hemorrhage / Q000097:blood* / Q000175:diagnosis; D011237:Predictive Value of Tests; D011379:Prognosis; D012189:Retrospective Studies; D012307:Risk Factors; D015607:Stents